A Data-Driven Cognitive Composite Sensitive to Amyloid-β for Preclinical Alzheimer’s Disease
Background: Integrating scores from multiple cognitive tests into a single cognitive composite has been shown to improve sensitivity to detect AD-related cognitive impairment. However, existing composites have little sensitivity to amyloid-β status (Aβ +/-) in preclinical […]
Predicting amyloid risk by machine learning algorithms based on the A4 screen data: Application to the Japanese Trial-Ready Cohort study
Background Selecting cognitively normal elderly individuals with higher risk of brain amyloid deposition is critical to the success of prevention trials for Alzheimer’s disease (AD). Methods Based on the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease study […]
